Country trachoma control programs are currently mass treating trachoma endemic communities every year using single dose azithromycin, with no evidence base for how long treatment must continue to reach these goals, or the optimal clinical marker with which to monitor progress. The World Health Organization currently suggests using follicular trachoma (TF) for monitoring, but data suggest this is sub-optimal. This application addresses the following critical aims for national programs: first, we determine the prevalence of infection in Tanzanian communities after exposure to mass treatment for 3 to 7 years, and whether an optimal number of yearly rounds can be identified after which mass treatment could be reconsidered. Second, we assess the utility and predictive value of specific combinations of clinical trachoma signs, following rounds of mass treatment that might be used to chart progress and guide decisions to stop mass treatment. Working with the Tanzania National Trachoma Control Program communities, we propose to survey samples within 18 communities in each of five strata, reflecting exposure to 3, 4, 5, 6, and 7 rounds of mass treatment. Within the 90 communities, a random sample of children age 1-7 years will be selected to serve as a sentinel sample of current status of trachoma and infection with ocular C. trachomatis, according to years of exposure to mass treatment. Analyses, using models adjusted for clustering of infection within villages, will determine the prevalence of infection as a function of years of exposure to mass treatment, treatment coverage over time, baseline prevalence of trachoma, and other village level predictors. Within strata of exposure to rounds of mass treatment, the utility of other clinical markers against infection, compared to the WHO-recommended use of TF alone against infection, will be assessed. The results are critical for National Trachoma Programs, who need a better understanding of infection in their communities following several rounds of mass treatment and better clinical markers to guide decisions of when to stop mass treatment. [unreadable] [unreadable]